Scandinavian Journal of Statistics, ISSN 0303-6898, 03/2017, Volume 44, Issue 1, pp. 21 - 45

Skew‐symmetric families of distributions such as the skew‐normal and skew‐t represent supersets of the normal and t distributions, and they exhibit richer...

angular density, asymptotic independence, extremal coefficient, extreme values, max‐stable distribution, non‐central extended skew‐t distribution, non‐stationarity, skew‐normal distribution, skew‐normal process, skew‐t distribution | angular density, asymptotic independence, extremal coefficient, extreme values, max-stable distribution, non-central extended skew-t distribution, non-stationarity, skew-normal distribution, skew-normal process, skew-t distribution | FIELDS | max-stable distribution | skew-t distribution | STATISTICS | skew-normal distribution | REPRESENTATION | STATISTICS & PROBABILITY | NORMAL DISTRIBUTIONS | non-central extended skew-t distribution | non-stationarity | extreme values | angular density | extremal coefficient | VALUES | MAX-STABLE PROCESSES | skew-normal process | asymptotic independence | MULTIVARIATE EXTREMES | Studies | Normal distribution | Statistical analysis | Covariance | Mathematical models | Spectra | Behavior | Representations | Statistics | Density | Handling

angular density, asymptotic independence, extremal coefficient, extreme values, max‐stable distribution, non‐central extended skew‐t distribution, non‐stationarity, skew‐normal distribution, skew‐normal process, skew‐t distribution | angular density, asymptotic independence, extremal coefficient, extreme values, max-stable distribution, non-central extended skew-t distribution, non-stationarity, skew-normal distribution, skew-normal process, skew-t distribution | FIELDS | max-stable distribution | skew-t distribution | STATISTICS | skew-normal distribution | REPRESENTATION | STATISTICS & PROBABILITY | NORMAL DISTRIBUTIONS | non-central extended skew-t distribution | non-stationarity | extreme values | angular density | extremal coefficient | VALUES | MAX-STABLE PROCESSES | skew-normal process | asymptotic independence | MULTIVARIATE EXTREMES | Studies | Normal distribution | Statistical analysis | Covariance | Mathematical models | Spectra | Behavior | Representations | Statistics | Density | Handling

Journal Article

Computational Statistics and Data Analysis, ISSN 0167-9473, 2012, Volume 56, Issue 1, pp. 126 - 142

In this paper we consider a flexible class of models, with elements that are finite mixtures of multivariate skew-normal independent distributions. A general...

Skew-normal independent distributions | Skew-normal distribution | EM algorithm | Multivariate finite mixtures | MAXIMUM-LIKELIHOOD-ESTIMATION | SCALE MIXTURES | T-DISTRIBUTION | STATISTICS & PROBABILITY | EXTENSION | INFERENCE | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | ROBUST | CONVERGENCE | FINITE MIXTURES | IDENTIFIABILITY | EM algorithm Multivariate finite mixtures Skew-normal distribution Skew-normal independent distributions | Analysis | Models | Algorithms | Approximation | Asymptotic properties | Computation | Mathematical analysis | Mathematical models | Estimates | Statistics

Skew-normal independent distributions | Skew-normal distribution | EM algorithm | Multivariate finite mixtures | MAXIMUM-LIKELIHOOD-ESTIMATION | SCALE MIXTURES | T-DISTRIBUTION | STATISTICS & PROBABILITY | EXTENSION | INFERENCE | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | ROBUST | CONVERGENCE | FINITE MIXTURES | IDENTIFIABILITY | EM algorithm Multivariate finite mixtures Skew-normal distribution Skew-normal independent distributions | Analysis | Models | Algorithms | Approximation | Asymptotic properties | Computation | Mathematical analysis | Mathematical models | Estimates | Statistics

Journal Article

Journal of Multivariate Analysis, ISSN 0047-259X, 07/2018, Volume 166, pp. 98 - 110

We introduce a broad and flexible class of multivariate distributions obtained by both scale and shape mixtures of multivariate skew-normal distributions. We...

Skew-normal distribution | Shape mixtures of skew-normal distributions | Scale mixtures of skew-normal distributions | Skew scale mixtures of normal distributions | EM-algorithm | Scale mixtures of normal distributions | GENERAL-CLASS | ELLIPTIC DISTRIBUTIONS | STATISTICS & PROBABILITY | INFERENCE

Skew-normal distribution | Shape mixtures of skew-normal distributions | Scale mixtures of skew-normal distributions | Skew scale mixtures of normal distributions | EM-algorithm | Scale mixtures of normal distributions | GENERAL-CLASS | ELLIPTIC DISTRIBUTIONS | STATISTICS & PROBABILITY | INFERENCE

Journal Article

Statistics and Probability Letters, ISSN 0167-7152, 09/2015, Volume 104, pp. 75 - 81

We propose a new generalization of the skew-normal distribution (Azzalini, 1985) referred to as the Kumaraswamy skew-normal. The new distribution is...

Skew-normal distribution | Beta skew-normal distribution | Kumaraswamy distribution | Kumaraswamy skew-normal distribution | DENSITY | STATISTICS & PROBABILITY

Skew-normal distribution | Beta skew-normal distribution | Kumaraswamy distribution | Kumaraswamy skew-normal distribution | DENSITY | STATISTICS & PROBABILITY

Journal Article

British Journal of Mathematical and Statistical Psychology, ISSN 0007-1102, 05/2016, Volume 69, Issue 2, pp. 105 - 121

Maximum likelihood estimation of the linear factor model for continuous items assumes normally distributed item scores. We consider deviations from normality...

To be checked by Faculty | non‐normality | skew‐normal factor model | nonlinear factor model | skew‐normal distribution | Nonlinear factor model | Skew-normal distribution | Non-normality | Skew-normal factor model | MAXIMUM-LIKELIHOOD-ESTIMATION | TESTS | skew-normal distribution | STATISTICS & PROBABILITY | PSYCHOLOGY, EXPERIMENTAL | LATENT VARIABLE MODELS | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | skew-normal factor model | ESTIMATORS | STRUCTURAL EQUATION MODELS | PSYCHOLOGY, MATHEMATICAL | non-normality | Data Interpretation, Statistical | Reproducibility of Results | Psychiatric Status Rating Scales - standards | Humans | Male | Models, Statistical | Algorithms | Computer Simulation | Sensitivity and Specificity | Statistical Distributions | Psychometrics - methods | Adult | Female | Mental Disorders - diagnosis | Nonlinear Dynamics

To be checked by Faculty | non‐normality | skew‐normal factor model | nonlinear factor model | skew‐normal distribution | Nonlinear factor model | Skew-normal distribution | Non-normality | Skew-normal factor model | MAXIMUM-LIKELIHOOD-ESTIMATION | TESTS | skew-normal distribution | STATISTICS & PROBABILITY | PSYCHOLOGY, EXPERIMENTAL | LATENT VARIABLE MODELS | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | skew-normal factor model | ESTIMATORS | STRUCTURAL EQUATION MODELS | PSYCHOLOGY, MATHEMATICAL | non-normality | Data Interpretation, Statistical | Reproducibility of Results | Psychiatric Status Rating Scales - standards | Humans | Male | Models, Statistical | Algorithms | Computer Simulation | Sensitivity and Specificity | Statistical Distributions | Psychometrics - methods | Adult | Female | Mental Disorders - diagnosis | Nonlinear Dynamics

Journal Article

Communications in Statistics - Theory and Methods, ISSN 0361-0926, 06/2017, Volume 46, Issue 11, pp. 5612 - 5632

In this work, first some distributional properties of extended two-piece skew normal distributions are presented. Next we revisit the special case, that is...

two-piece skew normal | skew-normal | skew-Cauchy | 62E20 | Half-normal | uni/bimodal distribution | 62E15 | 60E05 | SKEW-NORMAL-DISTRIBUTION | uni | MODELS | FAMILIES | CAUCHY DISTRIBUTION | STATISTICS & PROBABILITY | bimodal distribution | HALF-NORMAL DISTRIBUTION | Random variables | Skew distributions | Statistical methods | Normal distribution | Statistics

two-piece skew normal | skew-normal | skew-Cauchy | 62E20 | Half-normal | uni/bimodal distribution | 62E15 | 60E05 | SKEW-NORMAL-DISTRIBUTION | uni | MODELS | FAMILIES | CAUCHY DISTRIBUTION | STATISTICS & PROBABILITY | bimodal distribution | HALF-NORMAL DISTRIBUTION | Random variables | Skew distributions | Statistical methods | Normal distribution | Statistics

Journal Article

Communications in Statistics - Theory and Methods, ISSN 0361-0926, 06/2013, Volume 42, Issue 12, pp. 2229 - 2244

We consider a new generalization of the skew-normal distribution introduced by Azzalini ( 1985 ). We denote this distribution Beta skew-normal (BSN) since it...

Balakrishnan skew-normal | Skew-normal distribution | Beta skew-normal | Order statistics | DENSITY | STATISTICS & PROBABILITY | 62E15 | 60E05 | Studies | Normal distribution | Statistics | Beta

Balakrishnan skew-normal | Skew-normal distribution | Beta skew-normal | Order statistics | DENSITY | STATISTICS & PROBABILITY | 62E15 | 60E05 | Studies | Normal distribution | Statistics | Beta

Journal Article

Statistics, ISSN 0233-1888, 07/2015, Volume 49, Issue 4, pp. 842 - 858

We consider a distribution obtained by combining two well-known mechanisms for generating skewed distributions. In this manner we arrive at a flexible model...

skew-normal distribution | doubly skewed | epsilon-skew-normal | two-piece skew-normal | MODELS | STATISTICS & PROBABILITY | EXTENSION | INFERENCE

skew-normal distribution | doubly skewed | epsilon-skew-normal | two-piece skew-normal | MODELS | STATISTICS & PROBABILITY | EXTENSION | INFERENCE

Journal Article

Computational Statistics and Data Analysis, ISSN 0167-9473, 2011, Volume 55, Issue 4, pp. 1791 - 1806

Spatial generalized linear mixed models are common in applied statistics. Most users are satisfied using a Gaussian distribution for the spatial latent...

Approximate Bayesian inference | Geostatistics | Closed skew normal distribution | Latent variables | MCMC | Spatial generalized linear mixed model | Skew normal distribution | MAXIMUM-LIKELIHOOD | LINEAR MIXED MODELS | STATISTICS & PROBABILITY | PREDICTION | DISTRIBUTIONS | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | ERROR | Approximate Bayesian inference Closed skew normal distribution Geostatistics Latent variables MCMC Skew normal distribution Spatial generalized linear mixed model | Approximation | Mathematical analysis | Normal distribution | Inference | Strategy | Gaussian | Mathematical models | Bayesian analysis | Statistics

Approximate Bayesian inference | Geostatistics | Closed skew normal distribution | Latent variables | MCMC | Spatial generalized linear mixed model | Skew normal distribution | MAXIMUM-LIKELIHOOD | LINEAR MIXED MODELS | STATISTICS & PROBABILITY | PREDICTION | DISTRIBUTIONS | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | ERROR | Approximate Bayesian inference Closed skew normal distribution Geostatistics Latent variables MCMC Skew normal distribution Spatial generalized linear mixed model | Approximation | Mathematical analysis | Normal distribution | Inference | Strategy | Gaussian | Mathematical models | Bayesian analysis | Statistics

Journal Article

Journal of the Royal Statistical Society. Series B (Statistical Methodology), ISSN 1369-7412, 1/1999, Volume 61, Issue 3, pp. 579 - 602

Azzalini and Dalla Valle have recently discussed the multivariate skew normal distribution which extends the class of normal distributions by the addition of a...

Discriminants | Maximum likelihood estimation | Gaussian distributions | Mathematical independent variables | Scalars | Matrices | Random variables | Parameterization | Skewed distribution | Statistics | Multivariate normal distribution | Elliptical distributions | Quadratic forms | Skewness | Skew normal distribution | elliptical distributions | KURTOSIS | quadratic forms | STATISTICS & PROBABILITY | multivariate normal distribution | skewness | skew normal distribution | Statistics - Methodology

Discriminants | Maximum likelihood estimation | Gaussian distributions | Mathematical independent variables | Scalars | Matrices | Random variables | Parameterization | Skewed distribution | Statistics | Multivariate normal distribution | Elliptical distributions | Quadratic forms | Skewness | Skew normal distribution | elliptical distributions | KURTOSIS | quadratic forms | STATISTICS & PROBABILITY | multivariate normal distribution | skewness | skew normal distribution | Statistics - Methodology

Journal Article

Statistical Papers, ISSN 0932-5026, 5/2011, Volume 52, Issue 2, pp. 431 - 446

In this paper, we discuss a general class of skew two-piece skew-normal distributions, denoted by GSTPSN(λ1, λ2, ρ). We derive its moment generating function...

Generalized skew-normal distribution | Statistics for Business/Economics/Mathematical Finance/Insurance | Operations Research/Decision Theory | Generalized two-piece skew-normal distribution | Generalized skew two-piece skew-normal distribution | Economic Theory | Probability Theory and Stochastic Processes | Orthant probability | Skew-normal distribution | Unimodality and bimodality | Two-piece skew-normal distribution | Statistics | STATISTICS | REPRESENTATION | STATISTICS & PROBABILITY | Studies | Probability | Normal distribution | Generalized linear models | Paper | Theorems | Representations

Generalized skew-normal distribution | Statistics for Business/Economics/Mathematical Finance/Insurance | Operations Research/Decision Theory | Generalized two-piece skew-normal distribution | Generalized skew two-piece skew-normal distribution | Economic Theory | Probability Theory and Stochastic Processes | Orthant probability | Skew-normal distribution | Unimodality and bimodality | Two-piece skew-normal distribution | Statistics | STATISTICS | REPRESENTATION | STATISTICS & PROBABILITY | Studies | Probability | Normal distribution | Generalized linear models | Paper | Theorems | Representations

Journal Article

Environmetrics, ISSN 1180-4009, 11/2008, Volume 19, Issue 7, pp. 661 - 671

We develop a statistical model for the bias resulting from designing an air quality monitoring network with the aim of finding large values, and then using the...

closed skew‐normal distribution | tropospheric ozone | clean air act | extended skew‐normal distribution | Clean air act | Tropospheric ozone | Extended skew-normal distribution | Closed skew-normal distribution | ENVIRONMENTAL SCIENCES | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | SKEW-NORMAL DISTRIBUTION | STATISTICS & PROBABILITY | closed skew-normal distribution | extended skew-normal distribution

closed skew‐normal distribution | tropospheric ozone | clean air act | extended skew‐normal distribution | Clean air act | Tropospheric ozone | Extended skew-normal distribution | Closed skew-normal distribution | ENVIRONMENTAL SCIENCES | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | SKEW-NORMAL DISTRIBUTION | STATISTICS & PROBABILITY | closed skew-normal distribution | extended skew-normal distribution

Journal Article

13.
Full Text
MTPmle: A SAS macro and Stata programs for marginalized inference in semi-continuous data

Journal of Statistical Software, ISSN 1548-7660, 10/2018, Volume 87, Issue 6, pp. 1 - 24

We develop a SAS macro and equivalent Stata programs that provide marginalized inference for semi-continuous data using a maximum likelihood approach. These...

Semi-continuous | Log skew normal | Generalized gamma | Complex survey design | Marginalized two-part models | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | generalized gamma | STATISTICS & PROBABILITY | semi-continuous | MODEL | complex survey design | marginalized two-part models | log skew normal

Semi-continuous | Log skew normal | Generalized gamma | Complex survey design | Marginalized two-part models | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | generalized gamma | STATISTICS & PROBABILITY | semi-continuous | MODEL | complex survey design | marginalized two-part models | log skew normal

Journal Article

Journal of Pharmaceutical Sciences, ISSN 0022-3549, 10/2010, Volume 99, Issue 10, pp. 4351 - 4362

Most active pharmaceutical ingredients (API) exhibit particle size distributions with some degrees of asymmetry deviating from log-normality. A new...

content uniformity | particle size | heavy tail | log- skew-normal distribution | over potency | Monte-Carlo | low-dose drugs | log‐skew‐normal distribution | Monte–Carlo | low‐dose drugs | Low-dose drugs | Particle size | Over potency | Content uniformity | Heavy tail | Log-skew-normal distribution | HOMOGENEITY | DESIGN | CHEMISTRY, MEDICINAL | QUALITY | DOSAGE FORMS | OF-FIT TESTS | CHEMISTRY, MULTIDISCIPLINARY | TABLETS | SKEW-NORMAL DISTRIBUTION | log-skew-normal distribution | PHARMACOLOGY & PHARMACY | ETHINYLESTRADIOL | Dose-Response Relationship, Drug | Models, Theoretical | Particle Size | Risk | Monte Carlo Method | Drugs | Decay

content uniformity | particle size | heavy tail | log- skew-normal distribution | over potency | Monte-Carlo | low-dose drugs | log‐skew‐normal distribution | Monte–Carlo | low‐dose drugs | Low-dose drugs | Particle size | Over potency | Content uniformity | Heavy tail | Log-skew-normal distribution | HOMOGENEITY | DESIGN | CHEMISTRY, MEDICINAL | QUALITY | DOSAGE FORMS | OF-FIT TESTS | CHEMISTRY, MULTIDISCIPLINARY | TABLETS | SKEW-NORMAL DISTRIBUTION | log-skew-normal distribution | PHARMACOLOGY & PHARMACY | ETHINYLESTRADIOL | Dose-Response Relationship, Drug | Models, Theoretical | Particle Size | Risk | Monte Carlo Method | Drugs | Decay

Journal Article

Physica A: Statistical Mechanics and its Applications, ISSN 0378-4371, 02/2014, Volume 395, pp. 200 - 208

An asymptotic expression for the Kullback–Leibler (KL) divergence measure of multivariate skew-t distributions (MST) is derived. This novel class of flexible...

Heavy tails | Skew-normal | Kullback–Leibler divergence | Skew-[formula omitted] | Skewness | Kullback-Leibler divergence | Skew-t | CORRELATION-MATRICES | SKEW-NORMAL DISTRIBUTIONS | PHYSICS, MULTIDISCIPLINARY | T-DISTRIBUTION | ENTROPY

Heavy tails | Skew-normal | Kullback–Leibler divergence | Skew-[formula omitted] | Skewness | Kullback-Leibler divergence | Skew-t | CORRELATION-MATRICES | SKEW-NORMAL DISTRIBUTIONS | PHYSICS, MULTIDISCIPLINARY | T-DISTRIBUTION | ENTROPY

Journal Article

Neurocomputing, ISSN 0925-2312, 06/2017, Volume 241, pp. 90 - 96

Amortized variational inference, whereby the inferred latent variable posterior distributions are parameterized by means of neural network functions, has...

Deep generative model | Variational inference | Semi-supervised learning | Restricted multivariate skew-Normal distribution | SKEW-NORMAL-DISTRIBUTION | MIXTURE | RECOGNITION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Electrical engineering | Algorithms | Neural networks | Analysis

Deep generative model | Variational inference | Semi-supervised learning | Restricted multivariate skew-Normal distribution | SKEW-NORMAL-DISTRIBUTION | MIXTURE | RECOGNITION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Electrical engineering | Algorithms | Neural networks | Analysis

Journal Article

Statistics in Medicine, ISSN 0277-6715, 12/2014, Volume 33, Issue 28, pp. 4891 - 4903

In health services research, it is common to encounter semicontinuous data characterized by a point mass at zero followed by a right‐skewed continuous...

log‐skew‐normal distribution | semicontinuous data | two‐part model | weight loss intervention | health‐care expenditures | marginalized models | Weight loss intervention | Marginalized models | Two-part model | Semicontinuous data | Health-care expenditures | Log-skew-normal distribution | MEDICINE, RESEARCH & EXPERIMENTAL | MEDICAL INFORMATICS | two-part model | STATISTICS & PROBABILITY | ADO | DEMAND | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | health-care expenditures | EXPENDITURES | log-skew-normal distribution | MATHEMATICAL & COMPUTATIONAL BIOLOGY | HEALTH | Data Interpretation, Statistical | Likelihood Functions | United States | Veterans | Computer Simulation | Humans | Weight Reduction Programs - standards | Models, Statistical | Weight Reduction Programs - economics | Obesity - economics

log‐skew‐normal distribution | semicontinuous data | two‐part model | weight loss intervention | health‐care expenditures | marginalized models | Weight loss intervention | Marginalized models | Two-part model | Semicontinuous data | Health-care expenditures | Log-skew-normal distribution | MEDICINE, RESEARCH & EXPERIMENTAL | MEDICAL INFORMATICS | two-part model | STATISTICS & PROBABILITY | ADO | DEMAND | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | health-care expenditures | EXPENDITURES | log-skew-normal distribution | MATHEMATICAL & COMPUTATIONAL BIOLOGY | HEALTH | Data Interpretation, Statistical | Likelihood Functions | United States | Veterans | Computer Simulation | Humans | Weight Reduction Programs - standards | Models, Statistical | Weight Reduction Programs - economics | Obesity - economics

Journal Article

Journal of Computational and Applied Mathematics, ISSN 0377-0427, 05/2020, Volume 370, p. 112665

In statistical literature, the Gaussian process is used as a prior process to treat a non-linear regression from a Bayesian viewpoint with normally distributed...

Gaussian process regression | Closed skew normal distribution | Bayesian statistics | Prior distribution | Predictive distribution | MATHEMATICS, APPLIED

Gaussian process regression | Closed skew normal distribution | Bayesian statistics | Prior distribution | Predictive distribution | MATHEMATICS, APPLIED

Journal Article

Communications in Statistics - Theory and Methods, ISSN 0361-0926, 07/2017, Volume 46, Issue 14, pp. 7147 - 7156

In this paper, we propose a new bivariate distribution, namely bivariate alpha-skew-normal distribution. The proposed distribution is very flexible and capable...

bimodality | bivariate distributions | skew-normal distribution | 62E99 | asymmetry | Alpha-skew-normal distribution | STATISTICS & PROBABILITY | EXTENSION | Economic models | Normal distribution

bimodality | bivariate distributions | skew-normal distribution | 62E99 | asymmetry | Alpha-skew-normal distribution | STATISTICS & PROBABILITY | EXTENSION | Economic models | Normal distribution

Journal Article

Statistics in Medicine, ISSN 0277-6715, 05/2019, Volume 38, Issue 10, pp. 1715 - 1733

An efficient monotone data augmentation (MDA) algorithm is proposed for missing data imputation for incomplete multivariate nonnormal data that may contain...

generalized linear model | pattern mixture model | skew‐normal and skew‐t regression | tipping point analysis | Markov chain Monte Carlo | fully conditional specification | skew-normal and skew-t regression | MEDICINE, RESEARCH & EXPERIMENTAL | MEDICAL INFORMATICS | MISSING DATA | BINARY | STATISTICS & PROBABILITY | OBJECTIVE BAYESIAN-ANALYSIS | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | PRIOR DISTRIBUTIONS | MODELS | GIBBS SAMPLER | SENSITIVITY-ANALYSIS | MATHEMATICAL & COMPUTATIONAL BIOLOGY | MULTIPLE IMPUTATION | Markov processes | Monte Carlo method | Algorithms

generalized linear model | pattern mixture model | skew‐normal and skew‐t regression | tipping point analysis | Markov chain Monte Carlo | fully conditional specification | skew-normal and skew-t regression | MEDICINE, RESEARCH & EXPERIMENTAL | MEDICAL INFORMATICS | MISSING DATA | BINARY | STATISTICS & PROBABILITY | OBJECTIVE BAYESIAN-ANALYSIS | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | PRIOR DISTRIBUTIONS | MODELS | GIBBS SAMPLER | SENSITIVITY-ANALYSIS | MATHEMATICAL & COMPUTATIONAL BIOLOGY | MULTIPLE IMPUTATION | Markov processes | Monte Carlo method | Algorithms

Journal Article